Submicron Emitters Enable Reliable Quantification of Weak Protein–Glycan Interactions by ESI-MS
Bibliographic record
Abstract
Interactions between carbohydrates (glycans) and glycan-binding proteins (GBPs) regulate a wide variety of important biological processes. However, the affinities of most monovalent glycan–GBP complexes are typically weak (dissociation constant (Kd) > μM) and difficult to reliably measure with conventional assays; consequently, the glycan specificities of most GBPs are not well established. Here, we demonstrate how electrospray ionization mass spectrometry (ESI-MS), implemented with nanoflow ESI emitters with inner diameters of ∼50 nm, allows for the facile quantification of low-affinity glycan–GBP interactions. The small size of the droplets produced from these submicron emitters effectively eliminates the formation of nonspecific glycan–GBP binding (false positives) during the ESI process up to ∼mM glycan concentrations. Thus, interactions with affinities as low as ∼5 mM can be measured directly from the mass spectrum. The general suppression of nonspecific adducts (including nonvolatile buffers and salts) achieved with these tips enables ESI-MS glycan affinity measurements to be performed on C-type lectins, a class of GBPs that bind glycans in a calcium-dependent manner and are important regulators of immune response. At physiologically relevant calcium ion concentrations (2–3 mM), the extent of Ca2+ nonspecific adduct formation observed using the submicron emitters is dramatically suppressed, allowing glycan affinities, and the influence of Ca2+ thereon, to be measured. Finally, we show how the use of submicron emitters and suppression of nonspecific binding enable the quantification of labile (prone to in-source dissociation) glycan–GBP interactions.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".